Loitering detection using an associating pedestrian tracker in crowded scenes.
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| Title: | Loitering detection using an associating pedestrian tracker in crowded scenes. |
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| Authors: | Nam, Yunyoung1 |
| Source: | Multimedia Tools & Applications. May2015, Vol. 74 Issue 9, p2939-2961. 23p. |
| Subjects: | Object tracking (Computer vision), Loitering, Closed-circuit television, Television in security systems, Spatiotemporal processes |
| Abstract: | This paper presents a loitering detection method using an associating pedestrian tracker in public areas. We analyze the spatio-temporal characteristics to perform monitoring of people and generate alerts when loitering persons are detected. To determine and adjust a time threshold for raising an alarm, we obtain the mean time of stay for normal and abnormal situation. In addition, we consider an optimal threshold for staying time and escaping time to deal with various conditions. For object identification, we measure the mean square error and histogram of oriented gradients. In order to trace moving objects continuously, the HSI color model and a combination of Euclidean distance, color difference, and shape difference are measured based on consistent labeling tracking. To evaluate the performance of our method, we showed detection results of the PETS2007 dataset using thresholds obtained by our proposed methods. Our experiments show promising results with 75.45 % averaged recall rate and 87.12 % averaged precision rate were obtained in loitering objects. We also compared the proposed method to other reported methods. The experimental results showed a significant improvement on precision. [ABSTRACT FROM AUTHOR] |
| Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Loitering detection using an associating pedestrian tracker in crowded scenes. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Nam%2C+Yunyoung%22">Nam, Yunyoung</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>. May2015, Vol. 74 Issue 9, p2939-2961. 23p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Object+tracking+%28Computer+vision%29%22">Object tracking (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Loitering%22">Loitering</searchLink><br /><searchLink fieldCode="DE" term="%22Closed-circuit+television%22">Closed-circuit television</searchLink><br /><searchLink fieldCode="DE" term="%22Television+in+security+systems%22">Television in security systems</searchLink><br /><searchLink fieldCode="DE" term="%22Spatiotemporal+processes%22">Spatiotemporal processes</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper presents a loitering detection method using an associating pedestrian tracker in public areas. We analyze the spatio-temporal characteristics to perform monitoring of people and generate alerts when loitering persons are detected. To determine and adjust a time threshold for raising an alarm, we obtain the mean time of stay for normal and abnormal situation. In addition, we consider an optimal threshold for staying time and escaping time to deal with various conditions. For object identification, we measure the mean square error and histogram of oriented gradients. In order to trace moving objects continuously, the HSI color model and a combination of Euclidean distance, color difference, and shape difference are measured based on consistent labeling tracking. To evaluate the performance of our method, we showed detection results of the PETS2007 dataset using thresholds obtained by our proposed methods. Our experiments show promising results with 75.45 % averaged recall rate and 87.12 % averaged precision rate were obtained in loitering objects. We also compared the proposed method to other reported methods. The experimental results showed a significant improvement on precision. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-013-1763-7 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 2939 Subjects: – SubjectFull: Object tracking (Computer vision) Type: general – SubjectFull: Loitering Type: general – SubjectFull: Closed-circuit television Type: general – SubjectFull: Television in security systems Type: general – SubjectFull: Spatiotemporal processes Type: general Titles: – TitleFull: Loitering detection using an associating pedestrian tracker in crowded scenes. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Nam, Yunyoung IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 74 – Type: issue Value: 9 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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